A transmitting device and receiving device in a wireless communication system may transmit and receive information bits over a (communication) channel, by each executing processing such as described below with reference to FIG. 1. FIG. 1 is an exemplary diagram of a wireless communication system. The wireless communication system 1 includes a transmitting device 2 and a receiving device 3. The transmitting device 2 includes an encoding unit 21, a modulation mapping unit 22, and a transmission processing unit 23. The receiving device 3 includes a reception processing unit 31, a demodulation demapping unit 32, and a decoding unit 33.
The encoding unit 21 performs error-correction encoding of an information bit series to be transmitted, thereby generating an encoded bit series. For example, the encoding unit 21 generates an information bit series using turbo code which is defined as a data channel encoding format in Third Generation Partnership Project (3GPP).
Standard turbo code defined by the 3GPP is rate ⅓ turbo code. A turbo encoder includes two constituent encoders and an interleaver situated between the two constituent encoders. Constituent code is rate ½ recursive convolution code. The encoding unit 21 performs puncturing, where a part of parity bits output from the constituent encoders is not included in the code word. The encoding unit 21 may also execute repetition, where a part of parity bits output from the constituent decoders is repeated. Executing rate matching including puncturing and repetition enables an encoded bit series having an operational code rate to be generated in accordance with the communication quality of a communication channel 4 between the transmitting device 2 and receiving device 3.
The encoding unit 21 encodes the information bit series in increments of code blocks. We will say that the increment of data packets process each sub frame making up a wireless frame is a transport block. In a case where the size of the transport block exceeds a stipulated maximum size, the transport block is divided into multiple interleaver-size code blocks, and encoded by the encoding unit 21 in increments of code blocks.
The length of a wireless frame in Long Term Evolution (LTE) standardized under the 3GPP is 10 ms, and is made up of ten sub frames. User data of user equipment (UE) selected by scheduling of wireless resources is transmitted from an evolved Node B (eNodeB) to the UE, in increments of sub frames. The eNodeB may correspond to the transmitting device 2, and the UE may correspond to the receiving device 3. Sub frames include the Physical Downlink Control Channel (PDCCH) and Physical Downlink Shared Channel (PDSCH). The PDCCH is a channel to notify the UE selected by scheduling, of wireless allocation information. The PDSCH is a shared data channel for transmitting user data.
The modulation mapping unit 22 maps code bits to signal symbols by modulating the encoded bit series generated by the encoding unit 21 in increments of a predetermined number of bits, thereby generating a signal symbol series. Signal symbols are represented on a complex plane (signal space) as points which are different to corresponding original bit values before modulation processing.
Specifically, the modulation mapping unit 22 maps a sub block a predetermined number m from the first bit in the encoded bit series, to one signal symbol. For example, in Quadrature Phase Shift Keying (QPSK), m=2, in 16 Quadrature Amplitude Modulation (16QAM), m=4, and in 64QAM, m=6.
Signal symbols may be represented as complex numbers for the sake of convenience, with the real part and imaginary part of signal symbols represented as complex numbers being called “I channel component” and “Q channel component”, respectively. If we say that the encoded bit series b is b=(b0, b1, . . . bm-1) and the signal symbol s is s=(SI, SQ), code bits b0, b2, . . . bm-2 are mapped to the I channel component sI of the signal bits. Code bits b1, b3, . . . bm-1 are mapped to the Q channel component sQ of the signal bits. For example, in QPSK, the I channel component sI and the Q channel component sQ each correspond to one bit of code bit. On the other hand, in 16QAM and 64QAM, the I channel component sI and the Q channel component sQ each correspond to multiple bits of code bits. Thus, 16QAM and 64QAM are also called “multilevel modulation”.
The transmission processing unit 23 converts the signal symbol series generated by the modulation mapping unit 22 into carrier wave format wireless signals, and transmits the converted wireless signals to the communication channel 4.
The reception processing unit 31 receives the wireless signals transmitted from the transmitting device 2 over the communication channel 4, and performs reception processing on the received wireless signals. For example, the reception processing unit 31 performs linear amplification of the received wireless signals by auto gain control (AGC), and performs analog-to-digital (A/D) conversion of the linearly-amplified reception signals, so as to carry out synchronous detection. The reception processing unit 31 generates a reception symbol data series which may be expressed as points in signal space, by performing this reception processing on the received wireless signals, that is to say, on the received data series.
The demodulation demapping unit 32 obtains likelihood data serving as soft decision data corresponding to each bit on the information bit series transmitted from the transmitting device 2, and generates a likelihood data series (soft decision data) from the received bit series.
For example, if we assume that the communication channel 4 is an additive white Gaussian noise (AWGN) communication channel, the likelihood data may be calculated from the following expression. We will assume an average reception power Es, transmission symbol series si (i=0, 1, . . . , N−1 (where N is the code bit size)), AWGN noise signal ni, and variance σ2 of the noise signal ni. The reception signal series ri is expressed by the following Expression (1).ri=√{square root over (Es)}si+ni  (1)
The mean square of the noise signal ni is expressed by Expression (2), and the mean square of the transmission symbol series si is expressed by Expression (3).|ni|2=2σ2=N0  (2)|si|2=1  (3)
The transition probability P(rx|sx) (where X represents I channel component and Q channel component) from transmission symbol sx to reception symbol rx on the AWGN communication channel is expressed by the following Expression (4).
                              P          ⁡                      (                                          r                X                            |                              s                x                                      )                          =                              1                                          2                ⁢                π                ⁢                                                                  ⁢                                  σ                  2                                                              ⁢                      exp            ⁡                          (                                                -                                      1                                          2                      ⁢                                              σ                        2                                                                                            ⁢                                                      (                                                                  r                        X                                            -                                                                                                    E                            s                                                                          ⁢                                                  s                          X                                                                                      )                                    2                                            )                                                          (        4        )            
A likelihood data series yi is y0, y1, . . . ym-1, corresponding to the encoded bit series b0, b1, . . . , bm-1 to be mapped to the transmission symbol si. If we say that a code bit b, which is a transmission bit is 0 or 1, the likelihood data yi is defined by the following Expression (5) as a log-likelihood ratio.
                              y          i                =                  ln          ⁡                      (                                          P                ⁡                                  (                                                            b                      i                                        =                                          0                      |                                              r                        X                                                                              )                                                            P                ⁡                                  (                                                            b                      i                                        =                                          1                      |                                              r                        X                                                                              )                                                      )                                              (        5        )            
Applying the transition probability P(rx|sx) and probability computation rules to Expression (5), the likelihood data yi is defined by the following Expression (6). In the present specification, likelihood data numerically represented by a logarithm of posterior probability of likelihood in a case where different symbols are transmitted, will be referred to as standard scale (theoretical scale) or standard unit likelihood data.
                              y          i                =                  ln          (                                                    ∑                                                                            s                      X                                        :                                          b                      i                                                        =                  0                                            ⁢                              P                ⁡                                  (                                                            r                      X                                        |                                          s                      X                                                        )                                                                                    ∑                                                                            s                      X                                        :                                          b                      i                                                        =                  1                                            ⁢                              P                ⁡                                  (                                                            r                      X                                        |                                          s                      X                                                        )                                                              )                                    (        6        )            
The likelihood data yi, on the AWGN communication channel is expressed as in the following Expression (7) by applying Expression (4) to Expression (6).
                              y          i                =                  ln          (                                                    ∑                                                                            s                      X                                        :                                          b                      i                                                        =                  0                                            ⁢                              exp                ⁡                                  (                                                            -                                              1                                                  2                          ⁢                                                      σ                            2                                                                                                                ⁢                                                                  (                                                                              r                            X                                                    -                                                                                                                    E                                s                                                                                      ⁢                                                          s                              X                                                                                                      )                                            2                                                        )                                                                                    ∑                                                                            s                      X                                        :                                          b                      i                                                        =                  1                                            ⁢                              exp                ⁡                                  (                                                            -                                              1                                                  2                          ⁢                                                      σ                            2                                                                                                                ⁢                                                                  (                                                                              r                            X                                                    -                                                                                                                    E                                s                                                                                      ⁢                                                          s                              X                                                                                                      )                                            2                                                        )                                                              )                                    (        7        )            
Applying to the Expression (7) an approximation where only the dominant term yielding a maximum value for the sum is kept, approximates the likelihood data yi as in the following Expression (8),
                                                                        y                i                            =                            ⁢                                                                    max                                                                                            s                          X                                                :                                                  b                          i                                                                    =                      0                                                        ⁢                                      {                                                                  -                                                  1                                                      2                            ⁢                                                          σ                              2                                                                                                                          ⁢                                                                        (                                                                                    r                              X                                                        -                                                                                                                            E                                  s                                                                                            ⁢                                                              s                                X                                                                                                              )                                                2                                                              }                                                  -                                                                                                      ⁢                                                max                                                                                    s                        X                                            :                                              b                        i                                                              =                    1                                                  ⁢                                  {                                                            -                                              1                                                  2                          ⁢                                                      σ                            2                                                                                                                ⁢                                                                  (                                                                              r                            X                                                    -                                                                                                                    E                                s                                                                                      ⁢                                                          s                              X                                                                                                      )                                            2                                                        }                                                                                                        =                            ⁢                                                -                                                            E                      s                                                              N                      0                                                                      ⁢                                  {                                                                                    min                                                                                                            S                              I                                                        :                                                          b                              i                                                                                =                          0                                                                    ⁢                                                                        (                                                                                    r                              X                              ′                                                        -                                                          s                              X                                                                                )                                                2                                                              -                                                                  min                                                                                                            S                              I                                                        :                                                          b                              i                                                                                =                          1                                                                    ⁢                                                                        (                                                                                    r                              X                              ′                                                        -                                                          s                              X                                                                                )                                                2                                                                              }                                                                                        (        8        )            
where r′x is defined by the following Expression (9).rx′=rx/√{square root over (Es)}  (9)
The decoding unit 33 performs error-correction decoding processing using the soft decision data generated at the demodulation demapping unit 32, and estimates information bits transmitted from the transmitting device 2. For example, in a case where the encoding unit 21 has encoded an information bit series using turbo code such as described above, the decoding unit 33 may perform repetitive decoding processing where element decoding processing is repetitively performed. The decoding unit 33 may include a turbo decoder which executes this sort of processing.
A turbo decoder includes two constituent decoders corresponding to the two constituent encoders of the turbo encoder, and in order to realize consistency in order of the bit series, an interleaver and deinterleaver. A maximum a posteriori probability (MAP) algorithm, for example, is used for the constituent decoding processing by the constituent decoder. It is noted, however, that implementing a MAP algorithm to the constituent decoder without changing the format of the algorithm will result in increased design costs of the hardware for the constituent decoder. Accordingly, an algorithm modified to a format suitable for implementation is used. The turbo decoder executes decoding processing in increments of code blocks in the same way as the turbo encoder described above.
Now, modulation formats such as QPSK, 16QAM, and 64QAM, and code rates are dynamically changed in LTE, in accordance with the communication quality on the communication channel between the eNodeB and the UE. This technology is called adaptive modulation and coding (AMC).
Examples of transmission systems relating to the transmission antenna of the transmitting device 2 and the reception antenna of the receiving device 3 include single input single output (SISO), single input multi output (SIMO), and multi input multi output (MIMO). SISO is a transmission format configured by one transmission antenna and one reception antenna. SIMO is a transmission format configured by one transmission antenna and multiple reception antennas. MIMO is a transmission format configured by multiple transmission antennas and multiple reception antennas.
SIMO exhibits the diversity effect, by reception data including the same information being added to each other. SIMO yields likelihood data with improved signal to noise ratio (SNR) as compared to SISO,
In MIMO, mutually different information data is each transmitted from multiple transmission antennas, the transmitted mutually different information data is multiplexed on a multipath communication channel, and the multiplexed information data is received by each of the multiple reception antennas. Likelihood data corresponding to each bit of the signal symbols transmitted from each transmission antenna can each be received in MIMO, by the multiple reception data series received by the multiple reception antennas being demodulated at the same time.
For example, MIMO with a maximum number of four transmission antennas and four reception antennas is standardized in LTE, and rank adaptation may be applied, in which the number of transmission streams is controlled in accordance with the communication quality on the communication channel 4 between the transmitting device 2 and the receiving device 3.
In the wireless communication system 1 described above, likelihood data yi obtained applying Expression (6), such as likelihood data yi on an AWGN communication channel represented in Expression (7) or Expression (8), is likelihood data which has been strictly defined numerically, and is standard scale likelihood data. However, the likelihood data input to the decoding unit 33 after processing at the demodulation demapping unit 32 is implementation scale likelihood data yai which is different from the standard scale. This is due to the reception processing quantization processing, and so forth, at the reception processing unit 31. If we give a scale value (a scale ratio) sc to the ratio between the standard scale and implementation scale, the implementation scale likelihood data yai is obtained by the following Expression (10).yai=scyi  (10)
In a case where the decoding unit 33 may generate suitable decoded bits with low code error rate by performing decoding processing of input likelihood data by standard scale, the code error rate of decoded bits will be higher if the likelihood data input to the decoding unit 33 is implementation scale likelihood data yai. Accordingly, a scale value sc is preferably identified to convert the scale (units) from the implementation scale to the standard scale, in order to obtain suitable decoded bits from the implementation scale likelihood data yai.
For example, in a case where the modulation format used at the transmitting device 2 and receiving device 3 is QPSK, a technique to identify a scale value sc by the calculation described below.
Assuming a code bit series xi and SNR Sn, the likelihood data yi is represented by the following Expression (11).yi=Snxi+ni=Snri  (11)
Now, xi, ri, and Sn, are each defined as in Expressions (12) through (14).xi=±1  (12)ri=xi+ni  (13)Sn=SNR=Es/N0  (14)
On the other hand, the implementation scale likelihood data yai is defined as in the following Expression (15).yai=Ari  (15)
Substituting Expression (11) and Expression (15) into Expression (10) defines the scale value sc from the following Expression (16).sc=A/Sn  (16)
Now, the signal amplitude A and SNR in Expression (16) are obtained by the following calculation method.
First, the average of absolute values of the implementation scale likelihood data yai and the mean square of the implementation scale likelihood data yai may be calculated from the following Expressions (17) and (18), respectively.
                              〈                                                y              ai                                            〉                =                              1            N                    ⁢                                    ∑                              i                =                0                                            N                -                1                                      ⁢                                                        y                ai                                                                                      (        17        )                                          〈                      y            ai            2                    〉                =                              1            N                    ⁢                                    ∑                              i                =                0                                            N                -                1                                      ⁢                          y              ai              2                                                          (        18        )            
The average of absolute values of the implementation scale likelihood data yai and the mean square of the implementation scale likelihood data yai have a relation with variance σ2 of the noise signal ni and reception amplitude a, as indicated in the following Expressions (19) and (20).|yai=a×mag(σ)  (19)y2ai=a2(1+σ2)  (20)
Now, mag(σ) which is the amplitude of the standard variation σ of the noise ni is expressed as a complex function of the variance σ2 of the noise signal ni, so the decoder has a table indicating the relation between σ2 and mag(σ).
Based on the relation illustrated in Expressions (19) and (20), the signal amplitude A and SNR are obtained from the following Expressions (21) and (22).
                    A        =                              C            ×                          (                                                2                  q                                -                1                            )                                            mag            ⁡                          (              σ              )                                                          (        21        )                                SNR        =                  2          ⁢                                    a              2                        /                          σ              2                                                          (        22        )            
Here, C represents a fixed coefficient obtained beforehand by simulation, and q represents quantization bits.
The scale value sc is obtained by substituting Expressions (21) and (22) into Expressions (16).
See S. S. Pietrobon, “Implementation and performance of a turbo/MAP decoder”, http://www.itr.unisa.edu.au/˜steven/turbo/turboMAP.ps.gz, Aug. 29, 2012 confirmed by the inventor.